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I have been trying to declare a three dimensional array with the following constraints using numpy in Python 2.7.3:

1.) MyArray(First, Second, Third)

2.) First has 11 elements

3.) Second has 14 elements

4.a) The Third dimension varies in size depending on the element of the First dimension

4.b) If First=8 then Third=988

4.c) Else if First=10 or First=11 then Third=640

4.d) Else Third=494

Is this possible with arrays or should I be using structures?

Thank you in advance,

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  • according to the documentation, Several algorithms in NumPy work on arbitrarily strided arrays. However, some algorithms require single-segment arrays. When an irregularly strided array is passed in to such algorithms, a copy is automatically made.
    – Fabricator
    Commented Jul 25, 2014 at 0:51
  • @Fabricator - "Irregularly strided" doesn't mean that the shape can vary along an axis. (It's a bit too much to explain in a comment, but strides refers to how many memory steps to take to increment along a given axis.) Numpy arrays must have a regular shape. They can't be "ragged" (not counting object arrays, anyway).
    – Joe Kington
    Commented Jul 25, 2014 at 2:07
  • @JoeKington, thanks for the correction. Can you explain what is an irregularly strided array here?
    – Fabricator
    Commented Jul 25, 2014 at 2:43
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